Volunteer Summary

Table

Text

sets

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sets with group and time_point (formula: sets ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.38) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.18 (95% CI [18.52, 19.84], t(132) = 56.83, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.77, 95% CI [-0.17, 1.70], t(132) = 1.61, p = 0.107; Std. beta = 0.36, 95% CI [-0.08, 0.80])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.32, 95% CI [-1.11, 0.47], t(132) = -0.79, p = 0.428; Std. beta = -0.15, 95% CI [-0.53, 0.22])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.03, 95% CI [-1.20, 1.13], t(132) = -0.06, p = 0.954; Std. beta = -0.02, 95% CI [-0.57, 0.53])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

setv

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict setv with group and time_point (formula: setv ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.56) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.03 (95% CI [10.49, 11.56], t(132) = 40.58, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.38, 95% CI [-0.37, 1.14], t(132) = 1.00, p = 0.317; Std. beta = 0.23, 95% CI [-0.22, 0.68])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.25, 95% CI [-0.28, 0.79], t(132) = 0.93, p = 0.352; Std. beta = 0.15, 95% CI [-0.17, 0.47])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.18, 95% CI [-0.97, 0.61], t(132) = -0.45, p = 0.653; Std. beta = -0.11, 95% CI [-0.58, 0.36])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

maks

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict maks with group and time_point (formula: maks ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.73) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.26 (95% CI [43.03, 45.48], t(132) = 70.88, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.90, 95% CI [-0.83, 2.63], t(132) = 1.02, p = 0.309; Std. beta = 0.23, 95% CI [-0.22, 0.68])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.04, 95% CI [-0.94, 1.03], t(132) = 0.09, p = 0.931; Std. beta = 0.01, 95% CI [-0.24, 0.26])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.37, 95% CI [-1.08, 1.83], t(132) = 0.50, p = 0.615; Std. beta = 0.10, 95% CI [-0.28, 0.47])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ibs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ibs with group and time_point (formula: ibs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.61) and the part related to the fixed effects alone (marginal R2) is of 7.80e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.62 (95% CI [14.95, 16.28], t(132) = 46.05, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.05, 95% CI [-0.89, 0.99], t(132) = 0.11, p = 0.915; Std. beta = 0.02, 95% CI [-0.43, 0.48])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.19, 95% CI [-0.44, 0.82], t(132) = 0.59, p = 0.556; Std. beta = 0.09, 95% CI [-0.21, 0.39])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.27, 95% CI [-0.67, 1.21], t(132) = 0.57, p = 0.571; Std. beta = 0.13, 95% CI [-0.32, 0.58])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_e

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_e with group and time_point (formula: ers_e ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.33 (95% CI [11.89, 12.78], t(132) = 53.99, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.03, 95% CI [-0.66, 0.61], t(132) = -0.08, p = 0.937; Std. beta = -0.02, 95% CI [-0.47, 0.43])
• The effect of time point [2nd] is statistically significant and negative (beta = -0.52, 95% CI [-0.89, -0.15], t(132) = -2.78, p = 0.006; Std. beta = -0.37, 95% CI [-0.64, -0.11])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.51, 95% CI [-0.04, 1.06], t(132) = 1.82, p = 0.068; Std. beta = 0.36, 95% CI [-0.03, 0.75])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_r

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_r with group and time_point (formula: ers_r ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.47) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.33 (95% CI [10.87, 11.79], t(132) = 48.14, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.15, 95% CI [-0.50, 0.81], t(132) = 0.46, p = 0.644; Std. beta = 0.11, 95% CI [-0.34, 0.56])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.15, 95% CI [-0.66, 0.35], t(132) = -0.59, p = 0.554; Std. beta = -0.11, 95% CI [-0.46, 0.24])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.29, 95% CI [-0.46, 1.04], t(132) = 0.76, p = 0.447; Std. beta = 0.20, 95% CI [-0.32, 0.72])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_pa

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_pa with group and time_point (formula: pss_pa ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.48) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.41 (95% CI [42.98, 45.84], t(132) = 60.83, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.28, 95% CI [-0.74, 3.31], t(132) = 1.24, p = 0.214; Std. beta = 0.28, 95% CI [-0.16, 0.72])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -1.29, 95% CI [-2.87, 0.29], t(132) = -1.60, p = 0.109; Std. beta = -0.28, 95% CI [-0.62, 0.06])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.08, 95% CI [-2.41, 2.25], t(132) = -0.07, p = 0.945; Std. beta = -0.02, 95% CI [-0.52, 0.49])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_ps

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_ps with group and time_point (formula: pss_ps ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 26.51 (95% CI [24.23, 28.79], t(132) = 22.78, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -2.36, 95% CI [-5.59, 0.87], t(132) = -1.43, p = 0.152; Std. beta = -0.32, 95% CI [-0.76, 0.12])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 1.16, 95% CI [-1.06, 3.38], t(132) = 1.02, p = 0.306; Std. beta = 0.16, 95% CI [-0.14, 0.46])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.16, 95% CI [-4.44, 2.12], t(132) = -0.69, p = 0.488; Std. beta = -0.16, 95% CI [-0.60, 0.29])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss with group and time_point (formula: pss ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.63) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 45.10 (95% CI [41.70, 48.51], t(132) = 25.94, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -3.64, 95% CI [-8.46, 1.18], t(132) = -1.48, p = 0.139; Std. beta = -0.33, 95% CI [-0.77, 0.11])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 2.46, 95% CI [-0.77, 5.69], t(132) = 1.50, p = 0.135; Std. beta = 0.22, 95% CI [-0.07, 0.52])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.13, 95% CI [-5.90, 3.64], t(132) = -0.46, p = 0.642; Std. beta = -0.10, 95% CI [-0.54, 0.33])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_responsible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_responsible with group and time_point (formula: rki_responsible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.52) and the part related to the fixed effects alone (marginal R2) is of 8.24e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.82 (95% CI [19.67, 21.97], t(132) = 35.38, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.77, 95% CI [-0.86, 2.40], t(132) = 0.92, p = 0.355; Std. beta = 0.21, 95% CI [-0.24, 0.67])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.03, 95% CI [-1.18, 1.23], t(132) = 0.04, p = 0.967; Std. beta = 7.18e-03, 95% CI [-0.33, 0.34])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.32, 95% CI [-2.10, 1.46], t(132) = -0.35, p = 0.724; Std. beta = -0.09, 95% CI [-0.59, 0.41])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_nonlinear

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_nonlinear with group and time_point (formula: rki_nonlinear ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.59) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.21 (95% CI [12.32, 14.09], t(132) = 29.09, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.49, 95% CI [-0.77, 1.75], t(132) = 0.76, p = 0.448; Std. beta = 0.18, 95% CI [-0.28, 0.63])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.32, 95% CI [-1.19, 0.55], t(132) = -0.71, p = 0.477; Std. beta = -0.11, 95% CI [-0.43, 0.20])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.50, 95% CI [-0.79, 1.78], t(132) = 0.76, p = 0.447; Std. beta = 0.18, 95% CI [-0.28, 0.64])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_peer

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_peer with group and time_point (formula: rki_peer ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.55) and the part related to the fixed effects alone (marginal R2) is of 6.99e-04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.54 (95% CI [19.83, 21.25], t(132) = 56.89, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.10, 95% CI [-1.10, 0.90], t(132) = -0.20, p = 0.841; Std. beta = -0.05, 95% CI [-0.49, 0.40])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.69, 0.73], t(132) = 0.05, p = 0.956; Std. beta = 8.92e-03, 95% CI [-0.31, 0.33])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.14, 95% CI [-0.91, 1.19], t(132) = 0.26, p = 0.795; Std. beta = 0.06, 95% CI [-0.41, 0.53])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_expect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_expect with group and time_point (formula: rki_expect ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.30) and the part related to the fixed effects alone (marginal R2) is of 0.06. The model’s intercept, corresponding to group = control and time_point = 1st, is at 4.46 (95% CI [4.16, 4.76], t(132) = 28.99, p < .001). Within this model:

• The effect of group [treatment] is statistically significant and positive (beta = 0.46, 95% CI [0.04, 0.89], t(132) = 2.12, p = 0.034; Std. beta = 0.47, 95% CI [0.04, 0.91])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.18, 95% CI [-0.21, 0.56], t(132) = 0.89, p = 0.372; Std. beta = 0.18, 95% CI [-0.22, 0.58])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.02, 95% CI [-0.58, 0.55], t(132) = -0.06, p = 0.954; Std. beta = -0.02, 95% CI [-0.60, 0.56])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki with group and time_point (formula: rki ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.53) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 59.03 (95% CI [57.30, 60.75], t(132) = 67.23, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.62, 95% CI [-0.82, 4.05], t(132) = 1.30, p = 0.193; Std. beta = 0.30, 95% CI [-0.15, 0.76])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.10, 95% CI [-1.90, 1.70], t(132) = -0.11, p = 0.911; Std. beta = -0.02, 95% CI [-0.36, 0.32])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.28, 95% CI [-2.38, 2.94], t(132) = 0.21, p = 0.836; Std. beta = 0.05, 95% CI [-0.44, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_possible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_possible with group and time_point (formula: raq_possible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.50) and the part related to the fixed effects alone (marginal R2) is of 9.91e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.64 (95% CI [15.07, 16.21], t(132) = 53.75, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.13, 95% CI [-0.93, 0.68], t(132) = -0.31, p = 0.755; Std. beta = -0.07, 95% CI [-0.52, 0.38])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.31, 95% CI [-0.92, 0.30], t(132) = -0.99, p = 0.324; Std. beta = -0.17, 95% CI [-0.51, 0.17])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.66, 95% CI [-0.24, 1.56], t(132) = 1.43, p = 0.152; Std. beta = 0.37, 95% CI [-0.14, 0.87])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_difficulty

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_difficulty with group and time_point (formula: raq_difficulty ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 5.49e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.44 (95% CI [11.98, 12.89], t(132) = 53.50, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.26, 95% CI [-0.90, 0.39], t(132) = -0.78, p = 0.435; Std. beta = -0.18, 95% CI [-0.62, 0.27])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.02, 95% CI [-0.45, 0.42], t(132) = -0.08, p = 0.940; Std. beta = -0.01, 95% CI [-0.31, 0.29])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.21, 95% CI [-0.43, 0.86], t(132) = 0.64, p = 0.520; Std. beta = 0.15, 95% CI [-0.30, 0.59])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq with group and time_point (formula: raq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 5.45e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.08 (95% CI [27.13, 29.03], t(132) = 57.98, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.38, 95% CI [-1.73, 0.96], t(132) = -0.56, p = 0.574; Std. beta = -0.13, 95% CI [-0.58, 0.32])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.29, 95% CI [-1.21, 0.63], t(132) = -0.62, p = 0.536; Std. beta = -0.10, 95% CI [-0.40, 0.21])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.87, 95% CI [-0.48, 2.22], t(132) = 1.26, p = 0.208; Std. beta = 0.29, 95% CI [-0.16, 0.74])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

who

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict who with group and time_point (formula: who ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 2.11e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.95 (95% CI [13.59, 16.30], t(132) = 21.62, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.31, 95% CI [-1.61, 2.22], t(132) = 0.31, p = 0.753; Std. beta = 0.07, 95% CI [-0.38, 0.52])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.23, 95% CI [-1.35, 0.88], t(132) = -0.41, p = 0.683; Std. beta = -0.05, 95% CI [-0.32, 0.21])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.10, 95% CI [-1.75, 1.55], t(132) = -0.12, p = 0.907; Std. beta = -0.02, 95% CI [-0.41, 0.36])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

phq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict phq with group and time_point (formula: phq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.80) and the part related to the fixed effects alone (marginal R2) is of 5.28e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.72 (95% CI [2.62, 4.81], t(132) = 6.66, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.51, 95% CI [-2.06, 1.03], t(132) = -0.65, p = 0.516; Std. beta = -0.15, 95% CI [-0.59, 0.29])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.73, 0.78], t(132) = 0.06, p = 0.956; Std. beta = 6.10e-03, 95% CI [-0.21, 0.22])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.02, 95% CI [-1.10, 1.14], t(132) = 0.04, p = 0.972; Std. beta = 5.73e-03, 95% CI [-0.31, 0.33])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

gad

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict gad with group and time_point (formula: gad ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 6.10e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.28 (95% CI [2.28, 4.28], t(132) = 6.44, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.49, 95% CI [-1.90, 0.93], t(132) = -0.68, p = 0.499; Std. beta = -0.15, 95% CI [-0.60, 0.29])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.17, 95% CI [-0.66, 1.00], t(132) = 0.39, p = 0.694; Std. beta = 0.05, 95% CI [-0.21, 0.31])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.20, 95% CI [-1.03, 1.43], t(132) = 0.32, p = 0.751; Std. beta = 0.06, 95% CI [-0.32, 0.45])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_pcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_pcs with group and time_point (formula: nb_pcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.76) and the part related to the fixed effects alone (marginal R2) is of 7.96e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 51.43 (95% CI [49.07, 53.78], t(132) = 42.79, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -1.41, 95% CI [-4.75, 1.92], t(132) = -0.83, p = 0.405; Std. beta = -0.19, 95% CI [-0.63, 0.26])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.54, 95% CI [-2.30, 1.21], t(132) = -0.60, p = 0.546; Std. beta = -0.07, 95% CI [-0.31, 0.16])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 2.31, 95% CI [-0.29, 4.91], t(132) = 1.74, p = 0.082; Std. beta = 0.31, 95% CI [-0.04, 0.66])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_mcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_mcs with group and time_point (formula: nb_mcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.62) and the part related to the fixed effects alone (marginal R2) is of 4.23e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 50.39 (95% CI [47.76, 53.03], t(132) = 37.47, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.18, 95% CI [-2.55, 4.90], t(132) = 0.62, p = 0.536; Std. beta = 0.14, 95% CI [-0.31, 0.60])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.18, 95% CI [-2.63, 2.28], t(132) = -0.14, p = 0.887; Std. beta = -0.02, 95% CI [-0.32, 0.28])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.79, 95% CI [-4.42, 2.85], t(132) = -0.42, p = 0.671; Std. beta = -0.10, 95% CI [-0.54, 0.35])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Table